We evaluated our approach on three standard benchmark datasets MNIST [1]}, Fashion MNIST [2]} and CIFAR-10 [3]} . Both MNIST[1]} and Fashion MNIST[2]} are small 10 class datasets having \(60,000\)  training and \(10,000\)  test samples of size \(28\times 28\) . MNIST is a handwitten digits dataset, Fashion MNIST instead contains samples of apparels such as trouser, skirt, bag, ankle boot etc. The CIFAR-10 is another commonly used benchmarking dataset consisting of 6000 and 600 colour images (resolution \(32\times 32\) ) per class respectively including 1000 and 100 training samples per class respectively. CIFAR-10 contains samples of 4 vehicle and 6 animal classes http://groups.csail.mit.edu/vision/TinyImages/.
